Ari Kobren
Principal Research Scientist at Oracle
Cambridge, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolAri Kobren is a Principal Research Scientist at Oracle with 13 years of experience bridging machine learning research and deployable NLP systems. Trained at UMass Amherst (M.S./Ph.D.), he has a strong academic publication record and a history of industrial research internships at Google. His work spans probabilistic modeling and human-in-the-loop systems—evidenced by contributions to the FACTORIE toolkit that integrate human edits and user reliability into coreference resolution. Earlier roles include intelligence-focused NLP research at MIT Lincoln Laboratory and co-founding a campus-focused SaaS that scaled to hundreds of thousands of uses, showing an appetite for practical, user-facing solutions. Based in Cambridge, MA, he combines deep technical rigor with production-oriented engineering to move models from experiments into real systems. An unobvious strength: he has experience designing experiments and software that specifically model and leverage human annotation behavior, not just algorithmic performance.
13 years of coding experience
2 years of employment as a software developer
M.S./Ph.D Computer Science, M.S./Ph.D Computer Science at University of Massachusetts AmherstBachelor of Science Computer Science Engineering, Bachelor of Science Computer Science Engineering at Tufts University
Hebrew
Github Skills (5)
scala10
computer-engineering9
machine-learning9
data-structures8
data-structure8
Programming languages (8)
Github contributions (5)
factorie/factorie
Dec 2012 - May 2013
FACTORIE is a toolkit for deployable probabilistic modeling, implemented as a software library in Scala. It provides its users with a succinct language for creating relational factor graphs, estimating parameters and performing inference.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:14 commits in 5 months
Contributions summary:Ari's commits primarily focus on incorporating functionality to handle human edits within the Factorie toolkit. They've added classes and templates related to user reliability, edit sets, and the integration of human edits into the coreference resolution system. The user's changes involve modifications to existing data structures and code within the `HumanEdits.scala`, `Coref.scala`, and `Experiments.scala` files. They also made code changes to facilitate a user reliability experiment.
inferencescala
iesl/fair-matching
May 2019 - Jan 2020
Contributions:15 commits, 5 pushes in 8 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.